构建骨盆骨折患者术前深静脉血栓形成的列线图。
Construction of a nomogram for preoperative deep vein thrombosis in pelvic fracture patients.
机构信息
Dept. orthopedics trauma and hand surgery, the First Affiliated Hospital of Guangxi Medical University, NO. 6 ShuangYong Road, Nanning, 530022, Guangxi, China.
出版信息
BMC Surg. 2024 Oct 25;24(1):331. doi: 10.1186/s12893-024-02629-3.
BACKGROUND
In recent years, the incidence of pelvic fractures has been on the rise, predominantly affecting the elderly population. Deep vein thrombosis may lead to poor prognosis in patients. monocyte-to-lymphocyte ratio is novel biomarkers of inflammation, and this study aims to verify their predictive effect and construct the nomogram model.
METHOD
This study used binary logistic regression analysis to predict the predictive effect of MLR on the occurrence of DVT in pelvic fractures patients. And use R studio to construct nomogram model.
RESULT
The results showed that Age (1.04 [1.01, 1.07], p = 0.006), WBC (1.44 [1.28, 1.61], p < 0.001), and MLR (2.11 [1.08, 4.13], p = 0.029) were independent predictive factors. The nomogram demonstrated good predictive performance with small errors in both the training and validation groups, and most clinical patients could benefit from them.
CONCLUSION
The nomogram constructed based on MLR can assist clinicians in early assessment of the probability of DVT occurrence.
背景
近年来，骨盆骨折的发病率呈上升趋势，主要影响老年人群。深静脉血栓形成可能导致患者预后不良。单核细胞-淋巴细胞比值是炎症的新型生物标志物，本研究旨在验证其预测效果并构建列线图模型。
方法
本研究采用二项逻辑回归分析预测 MLR 对骨盆骨折患者 DVT 发生的预测效果，并使用 R 工作室构建列线图模型。
结果
结果表明，年龄（1.04 [1.01, 1.07]，p=0.006）、白细胞计数（1.44 [1.28, 1.61]，p<0.001）和 MLR（2.11 [1.08, 4.13]，p=0.029）是独立的预测因素。列线图在训练组和验证组中均显示出良好的预测性能，误差较小，大多数临床患者都能从中受益。
结论
基于 MLR 构建的列线图可以帮助临床医生早期评估 DVT 发生的概率。
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